Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 430878
Title A comprehensive view on climate change: coupling of Earth system and integrated assessment models
Author(s) Vuuren, D.P. van; Batlle Bayer, L.; Chuwah, C.; Ganzeveld, L.N.; Hazeleger, W.; Hurk, B. van den; Noije, T. van; O'Neill, B.; Strengers, B.J.
Source Environmental Research Letters 7 (2012)2. - ISSN 1748-9326
DOI http://dx.doi.org/10.1088/1748-9326/7/2/024012
Department(s) Earth System Science
Meteorology and Air Quality
WIMEK
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) carbon-cycle models - land-cover change - environmental-change - atmosphere-ocean - simpler model - scenarios - emissions - impact - feedbacks - dynamics
Abstract There are several reasons to strengthen the cooperation between the integrated assessment (IA) and earth system (ES) modeling teams in order to better understand the joint development of environmental and human systems. This cooperation can take many different forms, ranging from information exchange between research communities to fully coupled modeling approaches. Here, we discuss the strengths and weaknesses of different approaches and try to establish some guidelines for their applicability, based mainly on the type of interaction between the model components (including the role of feedback), possibilities for simplification and the importance of uncertainty. We also discuss several important areas of joint IA–ES research, such as land use/land cover dynamics and the interaction between climate change and air pollution, and indicate the type of collaboration that seems to be most appropriate in each case. We find that full coupling of IA–ES models might not always be the most desirable form of cooperation, since in some cases the direct feedbacks between IA and ES may be too weak or subject to considerable process or scenario uncertainty. However, when local processes are important, it could be important to consider full integration. By encouraging cooperation between the IA and ES communities in the future more consistent insights can be developed.
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